Steven Borg

The CMS ACCESS Model FHIR Implementation Guide is Up. My co-founder Hadi Javeed sat down with me last night and we pulled up the specs. Four API operations, seven subscription event types, twelve FHIR profiles. More impressive than that- he created an interactive sandbox for builders!! We mapped each operation against the clinical tracks, walked through the payment model line by line, and sketched out how we would integrate this into our software infrastructure. Then we wrote it up on The Techy Surgeon! I still believe the most compelling component to this model is the partnership architecture. An MSK practice collecting $180 per care episode while forgoing downstream surgical revenue of FFS billing is thin. Impractical as a standalone play. But an MSK practice or PT group that functions as the specialty care node in a broader value-based network -- receiving referrals from ACOs, coordinating with rehab partners for triage and PROM collection, with co-management payments flowing to the upstream entities that feed the pipeline and expanding their tech enabled capabilities -- that's a different model entirely. The ACCESS Model doesn't reward isolation. It rewards coordination. And the participants who build the network around them will be the ones who make the economics work. We're in the MSK and Behavioral Health tracks. The MSK improvement-only design with early success reporting at Day 185 maps directly to what we've built at RevelAi Health -- PROM trajectory monitoring, clinically informed AI powered patient engagement, distributed care coordination, partner data exchange. And the BH track opens an adjacent market where the same partnership-dependent architecture applies and the need for coordination infrastructure is even more acute. And yes, without AI -- it becomes impossible for this program to work for the ACCESS participant. Will this program actually enhance access? That remains to be seen, but we're determined to try. The full analysis and sandbox on The Techy Surgeon (link in comments). If you're an ACO, PT group, or specialty practice exploring ACCESS and want to talk partnership structures: hello@revelaihealth.com or visit us at the MSK ACCESS website (link in comments) #ACCESSModel #CMS #ValueBasedCare #FHIR #MSK #BehavioralHealth #DigitalHealth #CareCoordination

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Big Step, Daniel! SAMA’s 2025 momentum is clear: Version 1.0 of the use cases, risk evaluation framework, and implementation guide is now adopted. Participation includes 170+ participants across 35 states. Next up is a model state Medicaid AI policy aligned to NIST and built for real program operations. If your team wants a walkthrough or to learn more about SAMA, message me or Daniel and we'll set it up. #Medicaid #AI #ResponsibleAI #NIST #SAMA #AIinHealthcare

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When I look at the CMS roadmap for 2026 and 2027, it’s clear: healthcare industry has reached a point of no return. While much of the current discussion focuses on the "how" of FHIR API implementation, the real strategic challenge lies in the "why." Why are clinical decisions still being stalled by data silos in an era of instant connectivity? The mandate for a 72-hour turnaround on urgent Prior Authorizations is more than a regulatory hurdle. It is a real call to eliminate the friction that costs time, money, and, ultimately, patient outcomes. In our experience , meeting these deadlines shouldn't be treated as a painful compliance exercise. It is a unique opportunity to finally re-engineer the fragmented workflows that have slowed the industry down for decades. 2026 is here! The time to align technical infrastructure with clinical reality is now. How is your leadership team preparing for the shift from "storage" to "action"? #HealthTech #CMS #Interoperability #DigitalHealth #CEOInsights #ClinicalWorkflow #HealthIT #ITIRRA #AIDA

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Switching from prompt libraries to agent frameworks? Be ready for real learning. We’ve been deep in the weeds with Cloud Code SDK, learning agent patterns, sub-agents, orchestration flows (parallel, sequential, hybrid), and every “promising” pattern shared. It all looks amazing in a POC… until you try to use it in a real solution. The “perfect” orchestration pattern you hoped for still needs tuning, retries, and guardrails. There’s no silver bullet. Just steady experimentation, many failures, and slow, consistent learning about what works for your codebase. Don't build a fancy framework with routers, memory/state management, etc., until you can develop features with sub-agents & an orchestrator (and some patterns). After weeks of trial and refinement, we’re finally seeing consistent results (still ways to go). If you’re on this path, embrace the journey. Progress is real, but it takes time. One more: Experiment widely during R&D between Claude, Codex, and Antigravity (Google), but for production systems, pick one ecosystem and stay anchored. #AI #Engineering #Agents #CloudCode #LLM

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Top 9 Healthcare Data Exchange Guides for AI Professionals Healthcare data exchange is the backbone of modern medical innovation, enabling the seamless flow of health information across disparate systems and providers. By leveraging standardized protocols like HL7 FHIR for APIs and HL7 v2 for legacy messaging, organizations can break down data silos within EHRs like Epic and Cerner. For AI professionals, mastering these standards is not just a technical requirement—it is a strategic necessity to secure the high-quality, …...

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One question when buying clinical software: Where does accountability live? It breaks when context is split, ownership is unclear, or escalations rely on “someone noticed.” Look for structured handoffs, clear triggers, and audit trails not nice-to-have, a risk requirement. DM your letter for the checklist.

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Why Small Language Models (SLMs) Are Powering High-Precision Prior Authorization in Healthcare Prior authorization remains one of the most expensive and friction-heavy workflows in healthcare. The challenge isn’t lack of data — it’s precision. Large, general-purpose language models are impressive, but prior authorization demands something different: deep domain understanding, deterministic behavior, and consistent outcomes across payer-specific rules. This is where Small Language Models (SLMs) are proving to be far more effective. SLMs trained specifically on prior authorization workflows, payer policies, CPT and ICD mappings, medical necessity rules, and historical authorization outcomes can operate with significantly higher precision. They reduce hallucination risk, handle edge cases more reliably, and align better with compliance and audit requirements. More importantly, SLMs enable intent-driven automation. They can identify authorization requirements early, extract the exact clinical evidence needed, assemble payer-specific submissions, and flag gaps before a request ever reaches the payer. The result is fewer delays, fewer resubmissions, and faster patient access to care. Another advantage is deployability. SLMs are lighter, faster, and easier to operate in private or hybrid environments — a critical requirement for healthcare organizations that care about data control, latency, and regulatory boundaries. At Contiinex, we see prior authorization evolving from a manual, reactive process into a predictive, AI-assisted workflow powered by specialized SLMs — not generic models. #PriorAuthorization #HealthcareAI #SLMs #RevenueCycleManagement #DigitalHealth #Contiinex

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Anthropic released #Claude for #Healthcare today at #JPMHealthcare. Looks like a thoughtful set of agents with connected, commonly used data assets. Here's a summary from all four corners of the healthcare game board. **Providers** Claude offers HIPAA-ready infrastructure that enables healthcare organizations to deploy AI for workflows involving protected health information. - **Administrative efficiency**: Speeding up prior authorization requests and helping with patient care coordination to reduce pressures on clinicians’ time - **Database access**: Connections to ICD-10 codes for medical coding and billing accuracy, the National Provider Identifier Registry for credentialing and network management, and PubMed’s 35+ million biomedical articles for literature reviews - **Interoperability tools**: FHIR development agent skills to help connect healthcare systems faster with fewer errors - **Claims support**: Accelerating insurance appeals with structured reasoning and evidence synthesis **Patients** Claude can summarize patient-uploaded health records, explain test results in plain language, detect patterns across fitness and health metrics, and prepare questions for appointments . Additional features include: - Integration with Apple Health and Android Health Connect (rolling out in beta for Pro and Max subscribers) - Private by design with explicit opt-in required, and health data excluded from model training - Help navigating complex medical reports and understanding patterns over time **Pharma & Life Sciences** New capabilities for life sciences extend from preclinical R&D into clinical operations and regulatory affairs , including: - **Clinical trials**: Drafting clinical trial protocols and tracking trial indicators - **Regulatory submissions**: Helping with regulatory submissions so that more life saving drugs can come to market faster - **Scientific research**: Deep integrations with scientific databases and lab tools, with biosafety guardrails built in - Improved performance on spatial biology analysis and other life sciences benchmarks with the Claude Opus 4.5 model **Payers** Connectors to the Centers for Medicare & Medicaid Services Coverage Database enable Claude to verify locally-accurate coverage requirements and support prior authorization checks . Additional capabilities include: - Building stronger claims appeals - Support for revenue cycle and compliance teams - Prior authorization review agent skills that can be customized to organizational policies All standard #AI disclaimers apply. Always protect your #Data. https://lnkd.in/gZxQHd7h

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CMS didn’t just tweak the rules, they changed the entire rhythm of how Risk Adjustment Factor is earned… The new guidance is a clear signal: •No more scoring lift built on retroactive clean‑up. •No more coding heroics in Q4. •RAF is moving back to where it always should have lived. Inside real clinical encounters, documented in real time. What this means for organizations: • Documentation quality becomes a competitive advantage • Encounter data becomes the single source of truth AI and analytics shift from “finding codes” to supporting care teams • Operational discipline matters as much as clinical complexity RAF is becoming less about optimization and more about authenticity. Teams that embrace that shift early will be the ones shaping the next era of value‑based care.

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Flexpa just published our response to CMS and ASTP/ONC's request for information on the state of healthcare interop Drawing from our experience operating the nation's largest payer API network, we provide concrete recommendations for improving Blue Button 2.0, addressing USCDI implementation gaps, standardizing digital identity, and building sustainable network infrastructure Big thanks to Angela Liu for driving this internally and to Brendan Keeler for draft reviews https://lnkd.in/g6J-QAVJ

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